def chart(credit_list, time_list):
bar = Line("学生成绩平均绩点折线图\n")
bar.add("平均绩点GPA", time_list, credit_list, is_more_utils=True)
bar.show_config()
bar.render()
shutil.move('/home/fty/new-system/render.html',
'/home/fty/new-system/templates/student.html')
file = ""
with open('/home/fty/new-system/templates/student.html', 'r') as f:
hello = f.read()
file = hello
f.close()
head = '''
{% extends 'base.html' %}
{% block page_name %}你好,{{login_user}}{% endblock %}
{% block body_part3 %}
<a href="{{ url_for('student') }}" class="nav-link active">
{% endblock %}
{% block body_part1 %}
<span class="glyphicon glyphicon-stats"></span> 你好,{{login_user}}
{% endblock %}
{% block body_part2 %}
'''
with open('/home/fty/new-system/templates/student.html', 'w') as f1:
f1.write(head)
f1.write(file)
f1.write('\n')
f1.write("{% endblock %}")
def line_test(b, num):
X = pd.Series(unique(b)).values
Y = pd.Series(num.groupby(b).sum()).values
line = Line("香飘飘2019/04到2019/05月各省区经销商分销量")
line.add("", X, Y, mark_point=["average"])
line.show_config()
line.render("E:\\py_data_html\\line_test.html")
def chart(lists):
bar = Line("学生成绩平均绩点折线图")
bar.add("平均绩点GPA", ["大一（上）", "大一（下）", "大二（上）", "大二（下）", "大三（上）", "大三（下）"],
[lists[0], lists[1], lists[2], lists[3], lists[4], lists[5]],
is_more_utils=True)
bar.show_config()
bar.render()
shutil.move('/home/cris/new_system/render.html',
'/home/cris/new_system/templates/student.html')
file = ""
with open('/home/cris/new_system/templates/student.html', 'r') as f:
hello = f.read()
file = hello
f.close()
head = '''
{% extends 'base.html' %}
{% block page_name %}你好,{{login_user}}{% endblock %}
{% block body_part3 %}
<a href="{{ url_for('student') }}" class="nav-link active">
{% endblock %}
{% block body_part1 %}
<span class="glyphicon glyphicon-stats"></span> 你好,{{login_user}}
{% endblock %}
{% block body_part2 %}
'''
with open('/home/cris/new_system/templates/student.html', 'w') as f1:
f1.write(head)
f1.write(file)
f1.write('\n')
f1.write("{% endblock %}")
def statistics_for_op_length():
'''
本函数用以确定下面函数中的support的值
fc: 非流失玩家最大动作序列长度20219 最小序列长度1， 流失玩家最大序列长度7323 ，最小序列长度 1
选取的最小支持度是16，此时剔除掉了非流失玩家用户193 流失玩家用户1497
'''
from pyecharts import Line
fc_user_ops, fc_user_label, sc_user_ops, sc_user_label, tc_user_ops, tc_user_label, action_id = get_op_features_labels_from_pickle(
)
ops_length = [[], []]
[
ops_length[fc_user_label[user]].append(len(ops))
for user, ops in fc_user_ops.items()
]
user_length = [[], []]
c = [0, 0]
temp = [list(np.sort(ops_length[0])), list(np.sort(ops_length[1]))]
for support in range(1, max(ops_length[1])):
# 在1 和 max ops_length[1] 之间集中了大部分的游戏玩家
for i in [0, 1]:
for t in temp[i][c[i]:]:
if t <= support:
c[i] += 1
user_length[i].append(c[i])
line = Line()
index = [i for i in range(0, 100)]
line.add("非流失玩家", index, user_length[0][:100])
line.add("流失玩家", index, user_length[1][:100])
line.show_config()
line.render()
def get_line(item_name, subtitle, item_name_list, item_num_list):
line = Line(item_name,
subtitle,
title_text_size=30,
subtitle_text_size=25,
title_pos='center')
line.add("",
item_name_list,
item_num_list,
mark_point=["max", "min"],
mark_line=["average"],
title_pos='center',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
line.show_config()
grid = Grid(width=1300, height=800)
grid.add(line,
grid_top="13%",
grid_bottom="23%",
grid_left="15%",
grid_right="15%")
out_file_name = './analyse/' + item_name + '.html'
grid.render(out_file_name)
def chart(lists):
bar = Line("学生成绩平均绩点折线图")
bar.add(
"平均绩点GPA", ["大一（上）", "大一（下）", "大二（上）", "大二（下）", "大三（上）", "大三（下）"],
[lists[0], lists[1], lists[2], lists[3], lists[4], lists[5], lists[6]],
is_more_utils=True)
bar.show_config()
bar.render()
#shutil.move('/home/cris/system/flask/render.html','/home/cris/system/flask/templates/html')
with open('/home/cris/system/flask/render.html', 'r') as f:
hello = f.read()
abc = hello
with open('/home/cris/system/flask/templates/student.html', 'w') as f1:
f1.write("{% extends 'base.html' %}")
f1.write('\n')
f1.write("{% block page_name %}你好,{{login_user}}{% endblock %}")
f1.write('\n')
f1.write("{% block body_part1 %}你好,{{login_user}}{% endblock %}")
f1.write('\n')
f1.write("{% block body_part2 %}")
f1.write('\n')
f1.write(abc)
f1.write('\n')
f1.write("{% endblock %}")
def all_in_line(item_name, subtitle, _counter1, _counter2, _counter3):
line = Line(item_name,
subtitle,
title_text_size=30,
subtitle_text_size=18,
title_pos='center')
item_name_list, item_num_list = counter2seven_list(_counter1)
line.add("小群",
item_name_list,
item_num_list,
mark_point=["max"],
legend_pos='65%',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
item_name_list, item_num_list = counter2seven_list(_counter2)
line.add("大群",
item_name_list,
item_num_list,
mark_point=["max"],
legend_pos='65%',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
item_name_list, item_num_list = counter2seven_list(_counter3)
line.add("综合",
item_name_list,
item_num_list,
mark_point=["max"],
legend_pos='65%',
xaxis_interval=0,
xaxis_rotate=27,
xaxis_label_textsize=20,
yaxis_label_textsize=20,
yaxis_name_pos='end',
yaxis_pos="%50")
line.show_config()
grid = Grid(width=1300, height=800)
grid.add(line,
grid_top="13%",
grid_bottom="23%",
grid_left="15%",
grid_right="15%")
out_file_name = './analyse/' + item_name + '.html'
grid.render(out_file_name)
def draw_line():
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
line.add("商家C", attr, v1, is_step=True, is_label_show=True)
line.show_config()
line.render()
def test_line_user_define_marks():
line = Line("折线图示例")
line.add("商家A", CLOTHES, clothes_v1,
mark_point=["average", "max", "min"],
mark_point_symbol='diamond', mark_point_textcolor='#40ff27')
line.add("商家B", CLOTHES, clothes_v2,
mark_point=["average", "max", "min"],
mark_point_symbol='arrow', mark_point_symbolsize=40)
line.show_config()
line.render()
def create_simple_line():
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
print(News.objects.all())
return line
def draw_line(self, figure_name):
x_axis = []
points = []
for i in self.item_collection:
x_axis.append(i['dealDate'][0])
points.append(i['unitPrice'][0])
line = Line(figure_name)
line.add(figure_name, x_axis, points)
line.show_config()
line.render(figure_name + '.html')
def drawPicture(self, file):
df = pd.read_excel(file)
df = pd.DataFrame(df)
df.fillna(0, inplace=True)
df['曹操'] = df['曹操'] + df['丞相'] + df['操大怒'] + df['曹丞相'] + df['操大喜']
df['诸葛亮'] = df['诸葛亮'] + df['孔明曰'] + df['孔明笑'] + df['孔明']
df['刘备'] = df['刘备'] + df['玄德'] + df['玄德曰'] + df['主公'] + df['刘皇叔'] + \
df['刘玄德'] + df['玄德大'] + df['玄德问'] + df['刘豫州'] + df['玄德闻'] + df['玄德乃']
df['关云长'] = df['关云长'] + df['云长'] + df['关公']
df['赵云'] = df['赵子龙'] + df['子龙'] + df['赵云']
df['司马懿'] = df['司马懿'] + df['仲达'] + df['司马']
df['周瑜'] = df['公瑾'] + df['周瑜']
df['张飞'] = df['张飞'] + df['翼德']
del ([
df['丞相'], df['操大怒'], df['曹丞相'], df['操大喜'], df['孔明曰'], df['孔明笑'],
df['孔明'], df['玄德'], df['玄德曰'], df['主公'], df['刘皇叔'], df['刘玄德'],
df['玄德大'], df['玄德问'], df['刘豫州'], df['玄德闻'], df['玄德乃'], df['云长'],
df['关公'], df['赵子龙'], df['子龙'], df['仲达'], df['司马'], df['公瑾'],
df['翼德']
])
data = pd.DataFrame(df)
kings = ['曹操', '刘备', '孙权', '司马懿']
shuGuo = ['刘备', '关云长', '张飞', '诸葛亮']
x = [i for i in range(120)]
s = Scatter('四位当权者活跃回')
for king in kings:
s.add('{}'.format(king),
x,
data[king],
xaxis_rotate=60,
symbol_size=4)
s.show_config()
s.render('四位当权者活跃回.html')
nameS = Line('蜀国')
for name in shuGuo:
nameS.add('{}'.format(name),
x,
data[name],
xaxis_rotate=60,
symbol_size=0,
area_opacity=0.6)
nameS.show_config()
nameS.render('蜀国.html')
def test_line_user_define_marks():
line = Line("折线图示例")
line.add("商家A",
CLOTHES,
clothes_v1,
mark_point=["average", "max", "min"],
mark_point_symbol='diamond',
mark_point_textcolor='#40ff27')
line.add("商家B",
CLOTHES,
clothes_v2,
mark_point=["average", "max", "min"],
mark_point_symbol='arrow',
mark_point_symbolsize=40)
line.show_config()
line.render()
def draw(file_in, file_out):
'''
'''
df = pd.read_csv(file_in, encoding='utf-8')
print(type(df['留存比']))
print(df['留存比'].corr(df['随后中位数时间间隔']))
# 对每一条数据存如列表中
l1 = df['留存比'].tolist()
l1 = [e * 1000 for e in l1]
l2 = df['随后中位数时间间隔'].tolist()
attr = [i for i in range(len(l1))]
line = Line("")
line.add("流失留存比 * 1000", attr, l1)
line.add("卡顿时间", attr, l2)
line.show_config()
line.render(file_out)
def draw(self):
from pyecharts import Line
line = Line("")
churn_rates = []
intervals = []
for k, v in self.op_churn.items():
churn_rate = v[1] * 1.0 / v[0]
churn_rates.append(churn_rate)
intervals.append(self.op_intervals[k])
attr = [_ for _ in range(len(intervals))]
churnrates = [rate * 1000 for rate in churn_rates]
new_intervals = [i for i in intervals[::10]]
new_churnrates = [c for c in churnrates[::10]]
attr = [i for i in range(0, len(intervals), 10)]
line = Line("")
line.add("动作随后时间间隔", attr, new_intervals)
line.add("动作留存比 * 1000", attr, new_churnrates)
line.show_config()
line.render('./output/render.html')
def draw_sentiment_pic(self,csv_file1,csv_file2):
attr1, val1 = [], []
attr2, val2 = [], []
info1 = count_sentiment(csv_file1)
info2 = count_sentiment(csv_file2)
#字典的items()返回可遍历的(键, 值) 元组数组。
info1 = sorted(info1.items(), key=lambda x: x[0], reverse=False) # dict按照键值排序方法
info2 = sorted(info2.items(), key=lambda x: x[0], reverse=False) # dict按照键值排序方法
for each in info1[:-1]:
attr1.append(each[0])
val1.append(each[1])
for each in info2[:-1]:
attr2.append(each[0])
val2.append(each[1])
line = Line("豆瓣影评情感分析图")
#line.add("", attr, val, is_smooth=True, is_more_utils=True)
line.add("红海行动", attr1, val1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None)
line.add("我不是药神", attr2, val2, is_fill=True, area_color='#000', area_opacity=0.3, is_smooth=True)
line.show_config()
line.render("豆瓣影评情感分析图.html")
def draw_fill():
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图-面积图示例")
line.add("商家A",
attr,
v1,
is_fill=True,
line_opacity=0.2,
area_opacity=0.4,
symbol=None)
line.add("商家B",
attr,
v2,
is_fill=True,
area_color='#000',
area_opacity=0.3,
is_smooth=True)
line.show_config()
line.render()
def run():
getCSV()
a , b = wordcount(list_type)
m, n = wordcount(list_are)
# # 词云
# wordcloud = WordCloud(width=1300, height=620)
# wordcloud.add("", a, b, word_size_range=[20, 100])
# wordcloud.show_config()
# wordcloud.render()
# 柱形表
# bar = Bar("链家二手房_户型图表", "**************")
# # bar = Bar("我的第一个图表", "这里是副标题")
# bar.add("楼盘户型", a, b)
# bar.show_config()
# bar.render()
# attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
# v1 = [11, 12, 13, 10, 10, 10]
# pie = Pie("饼图示例")
# pie.add("", a, b, is_label_show=True)
# pie.show_config()
# pie.render()
# line = Line("折线图-面积图示例")
# line.add("商家A", a, b, is_fill=True, line_opacity=2000000, area_opacity=4000000, symbol=None)
# # line.add("商家B", m, n, is_fill=True, area_color='#000',line_opacity=200000, area_opacity=300000, symbol=None)
# line.show_config()
# line.render()
line = Line("折线图示例")
line.add("价格", a, b, mark_point=["average"])
# line.add("", m, n, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
line = Line("折线图-阶梯图示例")
line.add("价格", a, b, is_step=True, is_label_show=True)
# line.add("商家A", attr, v1, is_step=True, is_label_show=True)
line.show_config()
line.render()
def draw_line_mark():
attr = [
'周一',
'周二',
'周三',
'周四',
'周五',
'周六',
'周日',
]
line = Line("折线图示例")
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
yaxis_formatter="°C")
line.show_config()
line.render()
def test_line():
# line_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
# line_1
line = Line("折线图-数据堆叠示例")
line.add("商家A", attr, v1, is_stack=True, is_label_show=True)
line.add("商家B", attr, v2, is_stack=True, is_label_show=True)
line.show_config()
line.render()
# line_2
line = Line("折线图-阶梯图示例")
line.add("商家A", attr, v1, is_step=True, is_label_show=True)
line.show_config()
line.render()
# # line_3
line = Line("折线图-面积图示例")
line.add("商家A", attr, v1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None)
line.add("商家B", attr, v2, is_fill=True, area_color='#000', area_opacity=0.3, is_smooth=True)
line.show_config()
line.render()
# line_4
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日', ]
line = Line("折线图示例")
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"], mark_line=["average"])
line.show_config()
line.render()
def wc_access_visible():
start_time = datetime.datetime.strptime("1998-06-20 22:00:00", '%Y-%m-%d %H:%M:%S')
end_time = datetime.datetime.strptime("1998-06-25 22:00:00", '%Y-%m-%d %H:%M:%S')
attr = []
v1 = []
logs = open(results_dir + result_file_per_10_min_normalize_revised2, 'r')
for line_ in logs: # wc_day49_2.log,13/Jun/1998:14:39:52 +0000,415
# time_str = line.split(',')[1].split(' ')[0]
# time_line = datetime.datetime.strptime(time_str, '%d/%b/%Y:%H:%M:%S')
time_str = line_.split(',')[1] # wc_day60_1.out,23/Jun/1998:22:10,0.2395
time_line = datetime.datetime.strptime(time_str, '%d/%b/%Y:%H:%M')
if start_time < time_line < end_time:
attr.append(time_str)
v1.append(float(line_.split(',')[2]))
line = Line("WC Access per 10 Minute (Normalized) with Random", width=1600)
# line = Line("WC Access per 10 Minute", width=1600)
# line.add("A100", attr, v1, mark_point=["average"])
line.add("users", attr, v1, is_smooth=True, mark_line=["min", "max", "average"])
line.show_config()
line.render(results_dir + chart_file)
def crawl_mail(workQueue):
date = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time()))
attrs.append(date)
url = 'https://www.huobi.pro/zh-cn/eos_usdt/exchange/'
html = get_html(url)
# 创建request对象
soup = BeautifulSoup(html, 'lxml')
# 找出div中的内容
soup_text = soup.find('div', class_='coin_list')
btc, eth, eos, xrp = process_result(soup_text.text.strip())
send_text = btc + " |" + eth + " |" + eos + " |" + xrp
print send_text
workQueue.put(btc)
workQueue.put(eth)
workQueue.put(eos)
workQueue.put(xrp)
while workQueue.qsize() > 0:
print workQueue.qsize()
coin = workQueue.get()
results = coin.split(" ")
name = results[0]
price = results[1]
increase = results[2]
if cmp(name, "btc") == 0:
btcs.append(price)
elif cmp(name, "eos") == 0:
eoss.append(price)
elif cmp(name, "eth") == 0:
eths.append(price)
elif cmp(name, "xrp") == 0:
xrps.append(price)
alertMail(increase, price, send_text)
line = Line("huobi 主区大盘btc")
line.add("btc", attrs, btcs, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
time,
house,
mark_line=["average"],
mark_point=["max", "min"],
xaxis_name="日期",
yaxis_name="价格",
yaxis_name_gap=60)
x.add("地铁房",
time,
house1,
mark_point=["max", "min"],
xaxis_name="日期",
yaxis_name="价格",
yaxis_name_gap=60)
x.add("学区房",
time,
house2,
mark_point=["max", "min"],
xaxis_name="日期",
line_color='green',
yaxis_name="价格",
yaxis_name_gap=60)
x.add("车位房",
time,
house3,
mark_point=["max", "min"],
xaxis_name="日期",
yaxis_name="价格",
yaxis_name_gap=60)
x.show_config()
x.render()
def test_line():
# line_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
# line_0_1
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average", "max", "min"],
mark_point_symbol='diamond', mark_point_textcolor='#40ff27')
line.add("商家B", attr, v2, mark_point=["average", "max", "min"],
mark_point_symbol='arrow', mark_point_symbolsize=40)
line.show_config()
line.render()
# line_1
line = Line("折线图-数据堆叠示例")
line.add("商家A", attr, v1, is_stack=True, is_label_show=True)
line.add("商家B", attr, v2, is_stack=True, is_label_show=True)
line.show_config()
line.render()
# line_2
line = Line("折线图-阶梯图示例")
line.add("商家A", attr, v1, is_step=True, is_label_show=True)
line.show_config()
line.render()
# # line_3
line = Line("折线图-面积图示例")
line.add("商家A", attr, v1, is_fill=True, line_opacity=0.2, area_opacity=0.4, symbol=None)
line.add("商家B", attr, v2, is_fill=True, area_color='#000', area_opacity=0.3, is_smooth=True)
line.show_config()
line.render()
# line_4
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line = Line("折线图示例")
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"], mark_line=["average"])
line.show_config()
line.render()
def test_line():
# line_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
line = Line("折线图示例")
line.add("商家A", attr, v1, mark_point=["average"])
line.add("商家B", attr, v2, is_smooth=True, mark_line=["max", "average"])
line.show_config()
line.render()
# line_0_1
line = Line("折线图示例")
line.add("商家A",
attr,
v1,
mark_point=["average", "max", "min"],
mark_point_symbol='diamond',
mark_point_textcolor='#40ff27')
line.add("商家B",
attr,
v2,
mark_point=["average", "max", "min"],
mark_point_symbol='arrow',
mark_point_symbolsize=40)
line.show_config()
line.render()
# line_1
line = Line("折线图-数据堆叠示例")
line.add("商家A", attr, v1, is_stack=True, is_label_show=True)
line.add("商家B", attr, v2, is_stack=True, is_label_show=True)
line.show_config()
line.render()
# line_2
line = Line("折线图-阶梯图示例")
line.add("商家A", attr, v1, is_step=True, is_label_show=True)
line.show_config()
line.render()
# line_3
line = Line("折线图-面积图示例")
line.add("商家A",
attr,
v1,
is_fill=True,
line_opacity=0.2,
area_opacity=0.4,
symbol=None)
line.add("商家B",
attr,
v2,
is_fill=True,
area_color='#000',
area_opacity=0.3,
is_smooth=True)
line.show_config()
line.render()
# line_3_1
import math, random
line = Line("折线图示例")
line.add("商家A", attr,
[math.log10(random.randint(1, 99999)) for _ in range(6)])
line.add("商家B",
attr, [math.log10(random.randint(1, 99999999)) for _ in range(6)],
yaxis_type="log")
line.show_config()
line.render()
# line_4
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line = Line("折线图示例")
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"])
line.show_config()
line.render()
#提取中国从疫情开始每一疫情具体数据
tempBaseData = data["data"]["chinaDayList"]
#遍历每天具体数据编程pandas
for item in tempBaseData:
line = [
item["date"], item["confirm"], item["suspect"], item["dead"],
item["heal"], item["nowConfirm"], item["nowSevere"]
]
#创建pandas中的行
series = pd.Series(line, chinaDayColumnList)
chinaDaySeriesList.append(series)
#创建表格
chainDayDateFrame = pd.DataFrame(chinaDaySeriesList)
print(chainDayDateFrame)
#生成全国实时疫情趋势图
#创建折线图
line = Line("全国实时疫情趋势图", "人数", width=1200, height=600)
#从表格中拿到所以日期
dateAttr = list(chainDayDateFrame.loc[chainDayDateFrame.index, "date"])
confirm = list(chainDayDateFrame.loc[chainDayDateFrame.index, "confirm"])
suspect = list(chainDayDateFrame.loc[chainDayDateFrame.index, "suspect"])
nowConfirm = list(chainDayDateFrame.loc[chainDayDateFrame.index, "nowConfirm"])
nowSevere = list(chainDayDateFrame.loc[chainDayDateFrame.index, "nowSevere"])
line.add("累计确诊", dateAttr, confirm, mark_point=['max'])
line.add("现有疑似", dateAttr, suspect, mark_point=['max'])
line.add("现有确诊", dateAttr, nowConfirm, mark_point=['max'])
line.add("现有重症", dateAttr, nowSevere, mark_point=['max'])
line.show_config()
line.render(path="./output/全国实时疫情趋势图.html")
from pyecharts import Line, Bar, Pie, EffectScatter
# 数据
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 10, 100]
v2 = [55, 60, 16, 20, 15, 80]
# 普通折线图
line = Line('折线图')
line.add('商家A', attr, v1, mark_point=['max'])
line.add('商家B', attr, v2, mark_point=['min'], is_smooth=True)
line.show_config()
line.render(path='./data/01-04折线图.html')
# 阶梯折线图
line2 = Line('阶梯折线图')
line2.add('商家A', attr, v1, is_step=True, is_label_show=True)
line2.show_config()
line2.render(path='./data/01-05阶梯折线图.html')
# 面积折线图
line3 = Line("面积折线图")
line3.add("商家A",
attr,
v1,
is_fill=True,
line_opacity=0.2,
area_opacity=0.4,
symbol=None,
mark_point=['max'])
line3.add("商家B",
attr,
def read_content(file_name, filter_ip=['127.0.0.1']):
# 读取日志文件，并生成record和result以及可视化文件
# 过滤本地自动连接的IP
# 完成
li = []
# 所有数据
li_result = []
# 登录记录
log_type = []
# 密钥&密码登录
log_date_times = []
# 登录日期时间
log_ips = []
# 登录IP
log_ports = []
# 登录端口
log_dates = []
# 登录日期
log_times = []
# 登录时间
log_users = []
# 登录用户
log_sshds = []
# 登录号，匹配登出时间用
li_month = (('Jan ', '01-'), ('Feb ', '02-'), ('Mar ', '03-'), ('Apr ', '04-'), ('May ', '05-'), ('Jun ', '06-'), ('Jul ', '07-'), ('Aug ', '08-'), ('Sep ', '09-'), ('Oct ', '10-'), ('Nov ', '11-'), ('Dec ', '12-'))
# 替换日期
log_position = os.path.dirname(file_name)
print("reading the file: %s ..." % file_name, ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
try:
# 读取日志文件
with open(file_name , "rb") as f_code:
code = chardet.detect(f_code.readline())['encoding']
if code == "ascii":
code = "utf-8"
with open(file_name, "r", encoding=code, errors='ignore') as f:
content = str(f.read())
except Exception as e:
print("read the file : %s wrong!" % file_name, ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
return
for each in li_month:
content = content.replace(each[0], each[1])
# 月份格式替换成阿拉伯数字
li = content.split('\n')
li_close = []
close_port_format = re.compile('\[(.*?)\]')
close_time_format = re.compile("\d\d:\d\d:\d\d")
date_times_format = re.compile(".{0,8}\d\d:\d\d:\d\d")
ips_format = re.compile("\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}")
ports_format = re.compile("port (\d{1,})")
users_format = re.compile("for (.*?) from")
sshds_format = re.compile('\[(.*?)\]')
for each in li:
# 筛选登录记录
if "Accepted password" in each:
if re.findall(ips_format, each)[0] in filter_ip:
continue
li_result.append(each)
log_type.append("password")
# 密码登录
if "Accepted publickey" in each:
if re.findall(ips_format, each)[0] in filter_ip:
continue
li_result.append(each)
log_type.append("publickey")
# 密钥登录
if "session closed" in each and "sshd" in each:
# 登出记录
close_port = re.findall(close_port_format, each)[0]
close_user = each.split()[-1]
close_time = re.findall(close_time_format, each)[0]
li_close.append((close_port, close_user, close_time))
for each in li_result:
log_date_times.append(re.findall(date_times_format, each)[0])
log_ips.append(re.findall(ips_format, each)[0])
log_ports.append(re.findall(ports_format, each)[0])
log_users.append(re.findall(users_format, each)[0])
log_sshds.append(re.findall(sshds_format, each)[0])
for each in log_date_times:
log_dates.append(each[:-9])
log_times.append(each[-8:])
if log_dates:
# 计算年份
years = 0
log_dates.reverse()
start_month = log_dates[0].split('-')[0]
for i in range(len(log_dates)):
current_time = log_dates[i].split('-')
current_month = current_time[0]
if current_month > start_month:
years += 1
start_month = current_month
log_dates[i] = str(datetime.now().year - years)[-2:] + '-' + log_dates[i]
log_dates.reverse()
else:
print(file_name,":记录为空" , ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
print("read the file: %s complete" % file_name, ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
print("creating the file: %s ..." % str(log_position + "/record.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
with open(log_position + "/record.csv", "w", encoding="utf-8") as f:
head = "date,connect time,close time,use time,user,ip,port,longon type\n"
f.write(head)
for i in range(len(log_ips)):
try:
# 计算单次登录用时
log_out_time = "24:00:00"
for j in li_close:
if j[0] == log_sshds[i]:
log_out_time = li_close.pop(li_close.index(j))[2]
break
log_time_i_format = log_times[i].split(':')
close_time_i_format = log_out_time.split(':')
log_time_to_second = int(log_time_i_format[0])*3600 + int(log_time_i_format[1])*60 + int(log_time_i_format[2])
close_time_to_second = int(close_time_i_format[0])*3600 + int(close_time_i_format[1])*60 + int(close_time_i_format[2])
if log_out_time == "24:00:00":
use_time_to_second = 24*60*60 - log_time_to_second
elif close_time_to_second < log_time_to_second:
use_time_to_second = 24*3600 - log_time_to_second + close_time_to_second
else:
use_time_to_second = close_time_to_second - log_time_to_second
use_time = time_to_format(use_time_to_second)
contents = "%s,%s,%s,%s,%s,%s,%s,%s\n" % (log_dates[i], log_times[i], log_out_time, use_time, log_users[i], log_ips[i], log_ports[i], log_type[i])
except Exception as e:
contents = "%s,%s,-1,-1,%s,%s,%s,%s\n" % (log_dates[i], log_times[i], log_users[i], log_ips[i], log_ports[i], log_type[i])
finally:
f.write(contents)
print("create the file: %s complete" % str(log_position + "/record.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
print("reading the file: %s ..." % str(log_position + "/result.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
with open(log_position + "/record.csv", "r", encoding="utf-8") as f:
f.readline()
li_contents = f.read().split("\n")
li_contents_result = []
i = 0
for each in li_contents:
datas = each.split(',')
if datas[0] == "":
pass
elif not li_contents_result:
li_contents_result.append([datas[0], [datas[1], datas[2], datas[3]] + [1]])
i += 1
elif li_contents_result[i-1][0] != datas[0]:
li_contents_result.append([datas[0], [datas[1], datas[2], datas[3]] + [1]])
i += 1
else:
li_contents_result[i-1][1][-1] += 1
li_contents_result[i-1][1][1] = datas[2]
log_time_i_format = li_contents_result[i-1][1][2].split(':')
close_time_i_format = datas[3].split(':')
log_time_to_second = int(log_time_i_format[0])*3600 + int(log_time_i_format[1])*60 + int(log_time_i_format[2])
close_time_to_second = int(close_time_i_format[0])*3600 + int(close_time_i_format[1])*60 + int(close_time_i_format[2])
use_time_to_second = close_time_to_second + log_time_to_second
use_time = time_to_format(use_time_to_second)
li_contents_result[i-1][1][2] = use_time
with open(log_position + "/result.csv", "w", encoding="utf-8") as f:
head = "date,log time,logout time,day use time, logon times\n"
f.write(head)
li_dates = []
li_use_times = []
li_logon_times = []
for each in li_contents_result:
contents = "%s,%s,%s,%s,%d\n" % (each[0], each[1][0],each[1][1],each[1][2],each[1][3])
f.write(contents)
li_dates.append(each[0])
li_use_time_format = each[1][2].split(':')
li_use_time_to_second = int(li_use_time_format[0])*3600 + int(li_use_time_format[1])*60 + int(li_use_time_format[2])
if li_use_time_to_second/3600 > 24:
li_use_times.append(24)
else:
li_use_times.append(li_use_time_to_second/3600)
li_logon_times.append(each[1][3])
print("read the file: %s complete" % str(log_position + "/result.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
# 生成可视化文件
# 生成bar.js文件
print("creating the visual file: %s ..." % str(log_position + "/visual_bar.js"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
bar = Bar("登陆次数/日", "单位:次", width=1200, height=800)
bar.add("日期", li_dates, li_logon_times,is_more_utils=True)
config_bar = bar.show_config().replace("True", "true").replace("False", "false").replace("None", "null")
with open(log_position + "/visual_bar.js", "w", encoding="utf-8") as f:
content_bar = """var myChart_bar = echarts.init(document.getElementById('bar'));
var option_bar = """ + config_bar + ";\n" + "myChart_bar.setOption(option_bar);"
f.write(content_bar)
print("create the visual file: %s complete" % str(log_position + "/visual_bar.js"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
# 生成line.js文件
print("creating the visual file: %s ..." % str(log_position + "/visual.html"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
line = Line("总用时/日", "单位:小时", width=1200, height=800)
line.add("日期", li_dates, li_use_times,is_more_utils=True)
config_line = line.show_config().replace("True", "true").replace("False", "false").replace("None", "null")
with open(log_position + "/visual_line.js", "w", encoding="utf-8") as f:
content_line = """var myChart_line = echarts.init(document.getElementById('line'));
var option_line = """ + config_line + ";\n" + "myChart_line.setOption(option_line);"
f.write(content_line)
print("create the visual file: %s complete" % str(log_position + "/visual_line.js"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
# 生成visual_geo.csv/visual_geo_show.csv文件
print("creating the visual file: %s ..." % str(log_position + "/visual_geo.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
li_ips = []
set_ips = set()
di_ips = {}
di_locs = {}
with open(log_position + "/record.csv", "r", encoding="utf-8") as f:
f.readline()
for each in f.read().split('\n'):
each = each.split(',')
if each == '':
pass
elif len(each) == 8:
li_ips.append(each[-3])
set_ips = set(li_ips)
for ip in set_ips:
di_ips[ip] = li_ips.count(ip)
init_get_country()
content_geo = "loc,ip,经纬度,times\n"
content_geo_show = "loc,ip,经纬度,times\n"
for ip in di_ips.keys():
# 先过滤私有IP
if ip[:7] == "192.168" or ip[:3] == "127":
continue
elif ip[:3] == "172":
ip_each = ip.split('.')
if 16 <= int(ip_each[1]) <= 31:
continue
loc, lng_alt = get_loc(ip)
if loc == "" or lng_alt == "":
# 说明为国外地址，通过ip138查
loc, lng_alt = get_loc_ip138(ip)
if loc == "" or lng_alt == "":
# ip138再次查询失败
continue
content_geo += loc + "," + ip + "," + lng_alt + "," + str(di_ips[ip]) + "\n"
if loc not in di_locs:
# {位置:[[ip1,times],[ip2],times],...], all_times]}
di_locs[loc] = [lng_alt, [(ip, di_ips[ip])], di_ips[ip]]
else:
di_locs[loc][1].append((ip, di_ips[ip]))
di_locs[loc][2] += di_ips[ip]
# 地理图数据csv内容格式
# content_geo = """231,1.1.1.1,"116.397026,39.918058",1
# 231,1.1.1.1,"106.397026,0.918058",2
# 231,1.1.1.1,"156.397026,70.918058",3
# """
with open(log_position + "/visual_geo.csv", "w", encoding="utf-8") as f:
f.write(content_geo)
# 地理图csv内容格式
# 天津市,（106.47.98.130:9次，180.212.36.188:10次）,"117.21081309,39.14392990",9
# 地点，ip群（ip:次数，...），经纬度，总次数
# 源文件不变，再加一个汇总
for each in di_locs.keys():
content_geo_show += each + ",（"
for ip in di_locs[each][1]:
content_geo_show += ip[0] + " : " + str(ip[1]) + "次，"
content_geo_show += "）," + di_locs[each][0] + "," + str(di_locs[each][2]) + "\n"
with open(log_position + "/visual_geo_show.csv", "w", encoding="utf-8") as f:
f.write(content_geo_show)
print("create the visual file: %s complete" % str(log_position + "/visual_geo.csv"), ", time:", datetime.now().strftime('%Y-%m-%d %H:%M:%S'), file=open("./create_file_log", "a", encoding="utf-8"))
def test_grid():
# grid_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%")
line = Line("折线图示例", title_top="50%")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_top="50%")
bar.grid(line.get_series(), grid_top="60%")
bar.show_config()
bar.render()
# grid_1
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200, is_grid=True)
scatter.add("散点图示例", v1, v2, grid_left="60%", legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_pos="20%")
scatter.grid(es.get_series(), grid_right="60%")
scatter.show_config()
scatter.render()
# grid_2
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%", is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%", grid_left="60%")
bar.add("商家B",
attr,
v2,
is_stack=True,
grid_bottom="60%",
grid_left="60%",
legend_pos="80%")
line = Line("折线图示例")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"])
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6,
legend_top="50%",
legend_pos="20%")
bar.grid(line.get_series(), grid_bottom="60%", grid_right="60%")
bar.grid(scatter.get_series(), grid_top="60%", grid_left="60%")
bar.grid(es.get_series(), grid_top="60%", grid_right="60%")
bar.show_config()
bar.render()
# grid_3
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
grid_right="65%")
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="45%")
pie.add("",
attr,
v1,
radius=[30, 55],
legend_pos="65%",
legend_orient='vertical')
line.grid(pie.get_series(), grid_left="60%")
line.show_config()
line.render()
# grid_4
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温",
attr, [11, 11, 15, 13, 12, 13, 10],
mark_point=["max", "min"],
mark_line=["average"],
grid_right="60%")
line.add("最低气温",
attr, [1, -2, 2, 5, 3, 2, 0],
mark_point=["max", "min"],
mark_line=["average"],
legend_pos="20%",
grid_right="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
v1 = [[2320.26, 2320.26, 2287.3,
2362.94], [2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58,
2440.38], [2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_pos="60%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)],
v1,
legend_pos="80%")
line.grid(kline.get_series(), grid_left="55%")
line.show_config()
line.render()
# grid_5
import random
x_axis = [
"12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a",
"11a", "12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p",
"10p", "11p"
]
y_aixs = [
"Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday",
"Sunday"
]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", height=700, is_grid=True)
heatmap.add("热力图直角坐标系",
x_axis,
y_aixs,
data,
is_visualmap=True,
visual_top="45%",
visual_text_color="#000",
visual_orient='horizontal',
grid_bottom="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
heatmap.grid(bar.get_series(), grid_top="60%")
heatmap.show_config()
heatmap.render()
def test_grid():
# grid_0
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%")
line = Line("折线图示例", title_top="50%")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_top="50%")
bar.grid(line.get_series(), grid_top="60%")
bar.show_config()
bar.render()
# grid_1
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter(width=1200, is_grid=True)
scatter.add("散点图示例", v1, v2, grid_left="60%", legend_pos="70%")
es = EffectScatter()
es.add("动态散点图示例", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0],
effect_scale=6, legend_pos="20%")
scatter.grid(es.get_series(), grid_right="60%")
scatter.show_config()
scatter.render()
# grid_2
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", height=720, width=1200, title_pos="65%", is_grid=True)
bar.add("商家A", attr, v1, is_stack=True, grid_bottom="60%", grid_left="60%")
bar.add("商家B", attr, v2, is_stack=True, grid_bottom="60%", grid_left="60%", legend_pos="80%")
line = Line("折线图示例")
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"], mark_line=["average"])
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%")
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
scatter = Scatter("散点图示例", title_top="50%", title_pos="65%")
scatter.add("scatter", v1, v2, legend_top="50%", legend_pos="80%")
es = EffectScatter("动态散点图示例", title_top="50%")
es.add("es", [11, 11, 15, 13, 12, 13, 10], [1, -2, 2, 5, 3, 2, 0], effect_scale=6,
legend_top="50%", legend_pos="20%")
bar.grid(line.get_series(), grid_bottom="60%", grid_right="60%")
bar.grid(scatter.get_series(), grid_top="60%", grid_left="60%")
bar.grid(es.get_series(), grid_top="60%", grid_right="60%")
bar.show_config()
bar.render()
# grid_3
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"],
mark_line=["average"], grid_right="65%")
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [11, 12, 13, 10, 10, 10]
pie = Pie("饼图示例", title_pos="45%")
pie.add("", attr, v1, radius=[30, 55], legend_pos="65%", legend_orient='vertical')
line.grid(pie.get_series(), grid_left="60%")
line.show_config()
line.render()
# grid_4
line = Line("折线图示例", width=1200, is_grid=True)
attr = ['周一', '周二', '周三', '周四', '周五', '周六', '周日']
line.add("最高气温", attr, [11, 11, 15, 13, 12, 13, 10], mark_point=["max", "min"],
mark_line=["average"], grid_right="60%")
line.add("最低气温", attr, [1, -2, 2, 5, 3, 2, 0], mark_point=["max", "min"],
mark_line=["average"], legend_pos="20%", grid_right="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
value = [20, 40, 60, 80, 100, 120]
v1 = [[2320.26, 2320.26, 2287.3, 2362.94],
[2300, 2291.3, 2288.26, 2308.38],
[2295.35, 2346.5, 2295.35, 2345.92],
[2347.22, 2358.98, 2337.35, 2363.8],
[2360.75, 2382.48, 2347.89, 2383.76],
[2383.43, 2385.42, 2371.23, 2391.82],
[2377.41, 2419.02, 2369.57, 2421.15],
[2425.92, 2428.15, 2417.58, 2440.38],
[2411, 2433.13, 2403.3, 2437.42],
[2432.68, 2334.48, 2427.7, 2441.73],
[2430.69, 2418.53, 2394.22, 2433.89],
[2416.62, 2432.4, 2414.4, 2443.03],
[2441.91, 2421.56, 2418.43, 2444.8],
[2420.26, 2382.91, 2373.53, 2427.07],
[2383.49, 2397.18, 2370.61, 2397.94],
[2378.82, 2325.95, 2309.17, 2378.82],
[2322.94, 2314.16, 2308.76, 2330.88],
[2320.62, 2325.82, 2315.01, 2338.78],
[2313.74, 2293.34, 2289.89, 2340.71],
[2297.77, 2313.22, 2292.03, 2324.63],
[2322.32, 2365.59, 2308.92, 2366.16],
[2364.54, 2359.51, 2330.86, 2369.65],
[2332.08, 2273.4, 2259.25, 2333.54],
[2274.81, 2326.31, 2270.1, 2328.14],
[2333.61, 2347.18, 2321.6, 2351.44],
[2340.44, 2324.29, 2304.27, 2352.02],
[2326.42, 2318.61, 2314.59, 2333.67],
[2314.68, 2310.59, 2296.58, 2320.96],
[2309.16, 2286.6, 2264.83, 2333.29],
[2282.17, 2263.97, 2253.25, 2286.33],
[2255.77, 2270.28, 2253.31, 2276.22]]
kline = Kline("K 线图示例", title_pos="60%")
kline.add("日K", ["2017/7/{}".format(i + 1) for i in range(31)], v1, legend_pos="80%")
line.grid(kline.get_series(), grid_left="55%")
line.show_config()
line.render()
# grid_5
import random
x_axis = ["12a", "1a", "2a", "3a", "4a", "5a", "6a", "7a", "8a", "9a", "10a", "11a",
"12p", "1p", "2p", "3p", "4p", "5p", "6p", "7p", "8p", "9p", "10p", "11p"]
y_aixs = ["Saturday", "Friday", "Thursday", "Wednesday", "Tuesday", "Monday", "Sunday"]
data = [[i, j, random.randint(0, 50)] for i in range(24) for j in range(7)]
heatmap = HeatMap("热力图示例", height=700, is_grid=True)
heatmap.add("热力图直角坐标系", x_axis, y_aixs, data, is_visualmap=True, visual_top="45%",
visual_text_color="#000", visual_orient='horizontal', grid_bottom="60%")
attr = ["衬衫", "羊毛衫", "雪纺衫", "裤子", "高跟鞋", "袜子"]
v1 = [5, 20, 36, 10, 75, 90]
v2 = [10, 25, 8, 60, 20, 80]
bar = Bar("柱状图示例", title_top="52%")
bar.add("商家A", attr, v1, is_stack=True)
bar.add("商家B", attr, v2, is_stack=True, legend_top="50%")
heatmap.grid(bar.get_series(), grid_top="60%")
heatmap.show_config()
heatmap.render()
